text: // This file is part of Eigen, a lightweight C++ template library
  // for linear algebra.
  //
  // Copyright (C) 2014 Navdeep Jaitly <ndjaitly@google.com>
  //                    Benoit Steiner <benoit.steiner.goog@gmail.com>
  //
  // This Source Code Form is subject to the terms of the Mozilla
  // Public License v. 2.0. If a copy of the MPL was not distributed
  // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
  
  #ifndef EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H
  #define EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H
  namespace Eigen {
  
  /** \class TensorReverse
    * \ingroup CXX11_Tensor_Module
    *
    * \brief Tensor reverse elements class.
    *
    */
  namespace internal {
  template<typename ReverseDimensions, typename XprType>
  struct traits<TensorReverseOp<ReverseDimensions,
                                XprType> > : public traits<XprType>
  {
    typedef typename XprType::Scalar Scalar;
    typedef traits<XprType> XprTraits;
    typedef typename XprTraits::StorageKind StorageKind;
    typedef typename XprTraits::Index Index;
    typedef typename XprType::Nested Nested;
    typedef typename remove_reference<Nested>::type _Nested;
    static const int NumDimensions = XprTraits::NumDimensions;
    static const int Layout = XprTraits::Layout;
    typedef typename XprTraits::PointerType PointerType;
  };
  
  template<typename ReverseDimensions, typename XprType>
  struct eval<TensorReverseOp<ReverseDimensions, XprType>, Eigen::Dense>
  {
    typedef const TensorReverseOp<ReverseDimensions, XprType>& type;
  };
  
  template<typename ReverseDimensions, typename XprType>
  struct nested<TensorReverseOp<ReverseDimensions, XprType>, 1,
              typename eval<TensorReverseOp<ReverseDimensions, XprType> >::type>
  {
    typedef TensorReverseOp<ReverseDimensions, XprType> type;
  };
  
  }  // end namespace internal
  
  template<typename ReverseDimensions, typename XprType>
  class TensorReverseOp : public TensorBase<TensorReverseOp<ReverseDimensions,
                                            XprType>, WriteAccessors>
  {
    public:
    typedef typename Eigen::internal::traits<TensorReverseOp>::Scalar Scalar;
    typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
    typedef typename XprType::CoeffReturnType CoeffReturnType;
    typedef typename Eigen::internal::nested<TensorReverseOp>::type Nested;
    typedef typename Eigen::internal::traits<TensorReverseOp>::StorageKind
                                                                      StorageKind;
    typedef typename Eigen::internal::traits<TensorReverseOp>::Index Index;
  
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReverseOp(
        const XprType& expr, const ReverseDimensions& reverse_dims)
        : m_xpr(expr), m_reverse_dims(reverse_dims) { }
  
      EIGEN_DEVICE_FUNC
      const ReverseDimensions& reverse() const { return m_reverse_dims; }
  
      EIGEN_DEVICE_FUNC
      const typename internal::remove_all<typename XprType::Nested>::type&
      expression() const { return m_xpr; }
  
      EIGEN_DEVICE_FUNC
      EIGEN_STRONG_INLINE TensorReverseOp& operator = (const TensorReverseOp& other)
      {
        typedef TensorAssignOp<TensorReverseOp, const TensorReverseOp> Assign;
        Assign assign(*this, other);
        internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
        return *this;
      }
  
      template<typename OtherDerived>
      EIGEN_DEVICE_FUNC
      EIGEN_STRONG_INLINE TensorReverseOp& operator = (const OtherDerived& other)
      {
        typedef TensorAssignOp<TensorReverseOp, const OtherDerived> Assign;
        Assign assign(*this, other);
        internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
        return *this;
      }
  
    protected:
      typename XprType::Nested m_xpr;
      const ReverseDimensions m_reverse_dims;
  };
  
  // Eval as rvalue
  template<typename ReverseDimensions, typename ArgType, typename Device>
  struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device>
  {
    typedef TensorReverseOp<ReverseDimensions, ArgType> XprType;
    typedef typename XprType::Index Index;
    static const int NumDims = internal::array_size<ReverseDimensions>::value;
    typedef DSizes<Index, NumDims> Dimensions;
    typedef typename XprType::Scalar Scalar;
    typedef typename XprType::CoeffReturnType CoeffReturnType;
    typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
    static const int PacketSize = PacketType<CoeffReturnType, Device>::size;
  
    enum {
      IsAligned = false,
      PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
      BlockAccess = false,
      PreferBlockAccess = false,
      Layout = TensorEvaluator<ArgType, Device>::Layout,
      CoordAccess = false,  // to be implemented
      RawAccess = false
    };
  
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
                                                          const Device& device)
        : m_impl(op.expression(), device), m_reverse(op.reverse())
    {
      // Reversing a scalar isn't supported yet. It would be a no-op anyway.
      EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
  
      // Compute strides
      m_dimensions = m_impl.dimensions();
      if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
        m_strides[0] = 1;
        for (int i = 1; i < NumDims; ++i) {
          m_strides[i] = m_strides[i-1] * m_dimensions[i-1];
        }
      } else {
        m_strides[NumDims-1] = 1;
        for (int i = NumDims - 2; i >= 0; --i) {
          m_strides[i] = m_strides[i+1] * m_dimensions[i+1];
        }
      }
    }
  
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
    const Dimensions& dimensions() const { return m_dimensions; }
  
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
      m_impl.evalSubExprsIfNeeded(NULL);
      return true;
    }
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
      m_impl.cleanup();
    }
  
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index reverseIndex(
        Index index) const {
      eigen_assert(index < dimensions().TotalSize());
      Index inputIndex = 0;
      if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
        for (int i = NumDims - 1; i > 0; --i) {
          Index idx = index / m_strides[i];
          index -= idx * m_strides[i];
          if (m_reverse[i]) {
            idx = m_dimensions[i] - idx - 1;
          }
          inputIndex += idx * m_strides[i] ;
        }
        if (m_reverse[0]) {
          inputIndex += (m_dimensions[0] - index - 1);
        } else {
          inputIndex += index;
        }
      } else {
        for (int i = 0; i < NumDims - 1; ++i) {
          Index idx = index / m_strides[i];
          index -= idx * m_strides[i];
          if (m_reverse[i]) {
            idx = m_dimensions[i] - idx - 1;
          }
          inputIndex += idx * m_strides[i] ;
        }
        if (m_reverse[NumDims-1]) {
          inputIndex += (m_dimensions[NumDims-1] - index - 1);
        } else {
          inputIndex += index;
        }
      }
      return inputIndex;
    }
  
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(
        Index index) const  {
      return m_impl.coeff(reverseIndex(index));
    }
  
    template<int LoadMode>
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
    PacketReturnType packet(Index index) const
    {
      EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
      eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
  
      // TODO(ndjaitly): write a better packing routine that uses
      // local structure.
      EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type
                                                              values[PacketSize];
      for (int i = 0; i < PacketSize; ++i) {
        values[i] = coeff(index+i);
      }
      PacketReturnType rslt = internal::pload<PacketReturnType>(values);
      return rslt;
    }
  
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
      double compute_cost = NumDims * (2 * TensorOpCost::AddCost<Index>() +
                                       2 * TensorOpCost::MulCost<Index>() +
                                       TensorOpCost::DivCost<Index>());
      for (int i = 0; i < NumDims; ++i) {
        if (m_reverse[i]) {
          compute_cost += 2 * TensorOpCost::AddCost<Index>();
        }
      }
      return m_impl.costPerCoeff(vectorized) +
             TensorOpCost(0, 0, compute_cost, false /* vectorized */, PacketSize);
    }
  
    EIGEN_DEVICE_FUNC typename Eigen::internal::traits<XprType>::PointerType data() const { return NULL; }
  
    /// required by sycl in order to extract the accessor
    const TensorEvaluator<ArgType, Device> & impl() const { return m_impl; }
    /// added for sycl in order to construct the buffer from sycl device
    ReverseDimensions functor() const { return m_reverse; }
  
   protected:
    Dimensions m_dimensions;
    array<Index, NumDims> m_strides;
    TensorEvaluator<ArgType, Device> m_impl;
    ReverseDimensions m_reverse;
  };
  
  // Eval as lvalue
  
  template <typename ReverseDimensions, typename ArgType, typename Device>
  struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device>
      : public TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>,
                               Device> {
    typedef TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>,
                            Device> Base;
    typedef TensorReverseOp<ReverseDimensions, ArgType> XprType;
    typedef typename XprType::Index Index;
    static const int NumDims = internal::array_size<ReverseDimensions>::value;
    typedef DSizes<Index, NumDims> Dimensions;
  
    enum {
      IsAligned = false,
      PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
      BlockAccess = false,
      PreferBlockAccess = false,
      Layout = TensorEvaluator<ArgType, Device>::Layout,
      CoordAccess = false,  // to be implemented
      RawAccess = false
    };
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
                                                          const Device& device)
        : Base(op, device) {}
  
    typedef typename XprType::Scalar Scalar;
    typedef typename XprType::CoeffReturnType CoeffReturnType;
    typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
    static const int PacketSize = PacketType<CoeffReturnType, Device>::size;
  
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
    const Dimensions& dimensions() const { return this->m_dimensions; }
  
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
      return this->m_impl.coeffRef(this->reverseIndex(index));
    }
  
    template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
    void writePacket(Index index, const PacketReturnType& x) {
      EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
      eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
  
      // This code is pilfered from TensorMorphing.h
      EIGEN_ALIGN_MAX CoeffReturnType values[PacketSize];
      internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
      for (int i = 0; i < PacketSize; ++i) {
        this->coeffRef(index+i) = values[i];
      }
    }
  
  };
  
  
  }  // end namespace Eigen
  
  #endif // EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H
  